It is well known to employ block transform coding of digital images for bandwidth compression prior to transmission over a limited bandwidth communication channel. In a typical prior art digital image compression and transmission system employing block transform coding (see U.S. Pat. No. 4,302,775 issued Nov. 24, 1981 to Widergren et al), the digital image is formatted into blocks (e.g. 16.times.16 pixels) and a spatial frequency transformation such as a discrete cosine transform (DCT) is applied to each block to generate 16.times.16 blocks of transform coefficients. Each block of transform coefficients is ordered into a one-dimensional vector such that the frequencies represented by the coefficients generally increase along the vector. The transform coefficients are quantized and coded using a minimum redundancy coding scheme such as Huffman coding, and run length coding for runs of coefficients having zero magnitude. The coded transform coefficients are transmitted over the limited bandwidth channel.
At the receiver, the image signal is decoded using operations that are the inverse of those employed to encode the digital image. This technique is capable of producing advantageously high image compression ratios, thereby enabling low bit rate transmission of digital images over limited bandwidth communication channels.
It has been suggested that further improvements in image quality, without increasing the low bit rates, or alternatively even lower bit rates with the same quality of image, may be achieved by weighting the quantization of the transformed coefficients in accordance with the sensitivity of the human visual system to spatial frequencies (see "A Visual Weighted Cosine Transform for Image Compression and Quality Assessment" by N. B. Nill, IEEE Transactions on Communications, Vol. COM-33, pg. 551-557).
Block adaptive transform coding scheme have been proposed wherein transform blocks are sorted into classes by the level of image activity present in the blocks. Within each activity level, coding bits are allocated to individual transform coefficients with more bits being assigned to "busy" areas of the image and fewer bits assigned to "quiet" areas. (See "Adaptive Coding of Monochrome and Color Images" by W. H. Chen and C. H. Smith, IEEE Transactions on Communications, Vol. COM-25, No. 11, November 1977, pg 1285-1292). Although such block adaptive coding schemes achieve low overall bit rates, with low image distortion (in the sense of mean square error between the pixel values of the original image and the transmitted image) they fail to take into account the fact that transmission errors (e.g. quantization noise) in "busy" regions of the image are less visible than in "quiet" regions due to the phenomenon of frequency masking. U.S. Pat. No. 4,268,861 issued May 19, 1981, to Schreiber et al is an example of a non block transform image coding process that takes the frequency masking phenomenon into account. In the image coding system described by Schreiber et al, the image signal is separated into low, middle, and high frequency components. The low frequency component is finely quantized, and the high frequency component is coarsely quantized. Since the high frequency component contributes to image detail areas, the noise from the coarse quantization is hopefully less visible in such areas.
It is the object of the present invention to provide a block transform image compression technique that produces a further compression of the digital image. It is a further object of the present invention to provide a block transform image compression technique that takes advantage of the phenomenon of frequency masking, wherein noise is less visible in regions of an image having high frequency detail.